[1] "Alabama" "Alaska"
[3] "Arizona" "Arkansas"
[5] "California" "Colorado"
[7] "Connecticut" "Delaware"
[9] "Florida" "Georgia"
[11] "Hawaii" "Idaho"
[13] "Illinois" "Indiana"
[15] "Iowa" "Kansas"
[17] "Kentucky" "Louisiana"
[19] "Maine" "Maryland"
[21] "Massachusetts" "Michigan"
[23] "Minnesota" "Mississippi"
[25] "Missouri" "Montana"
[27] "Nebraska" "Nevada"
[29] "New Hampshire" "New Jersey"
[31] "New Mexico" "New York"
[33] "North Carolina" "North Dakota"
[35] "Ohio" "Oklahoma"
[37] "Oregon" "Pennsylvania"
[39] "Rhode Island" "South Carolina"
[41] "South Dakota" "Tennessee"
[43] "Texas" "Utah"
[45] "Vermont" "Virginia"
[47] "Washington" "West Virginia"
[49] "Wisconsin" "Wyoming"
SEER China vs others
https://www.rdocumentation.org/packages/bayesTFR/versions/6.1-2/topics/country.names
https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/state.html
If you want to see the code used in the analysis please click the code button on the right upper corner or throughout the page.
Select from the tabs below.
Aim:
Articles are downloaded as xml.
myTerm <- rstudioapi::terminalCreate(show = FALSE)
rstudioapi::terminalSend(
myTerm,
"xtract -input data/pubmed_result_SEER_MeSH.xml -pattern PubmedArticle -sep ' ' -def 'na' -element MedlineCitation/PMID PubDate/Year Affiliation> data/SEER_countries.csv \n"
)
Sys.sleep(1)
repeat {
Sys.sleep(0.1)
if (rstudioapi::terminalBusy(myTerm) == FALSE) {
print("Code Executed")
break
}
}library(readr)
SEER_countries <- read_delim("data/SEER_countries.csv",
"\t", escape_double = FALSE, col_names = c("PMID", "year", "Affiliations"),
na = "NA", trim_ws = TRUE)Parsed with column specification:
cols(
PMID = col_integer(),
year = col_character(),
Affiliations = col_character()
)
Parsed with column specification:
cols(
abb = col_character(),
country = col_character()
)
# deneme1 <- grepl(pattern = country[44], x = SEER_countries$Affiliations)
# deneme2 <- sapply(country, function(x) grepl(x, SEER_countries$Affiliations))
# sum(deneme1 != deneme2[,44])[1] 6240
At the time of the research the number of articles with ‘SEER Program’[Mesh] formula is 6240.
# deneme <- colSums(SEER_countries[,-(1:3)])
# deneme <- as.data.frame(deneme)
# deneme <- rownames_to_column(deneme, var = "countries")
# names(deneme) <- c("countries", "number")
# deneme %>% arrange(desc(number))